issue_comments: 451984471
This data as json
| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/2304#issuecomment-451984471 | https://api.github.com/repos/pydata/xarray/issues/2304 | 451984471 | MDEyOklzc3VlQ29tbWVudDQ1MTk4NDQ3MQ== | 971382 | 2019-01-07T16:04:11Z | 2019-01-07T16:04:11Z | NONE | Hi, thank you for your effort into making xarray a great library. As mentioned in the issue the discussion went on a PR in order to make xr.open_dataset parametrable. This post is about asking you about recommendations regarding our PR. In this case we would add a parameter to the open_dataset function called "force_promote" which is a boolean and False by default and thus not mandatory. And then spread that parameter down to the function maybe_promote in dtypes.py Where we say the following: if dtype.itemsize <= 2 and not force_promote: dtype = np.float32 else: dtype = np.float64 The downside of that is that we somehow pollute the code with a parameter that is used in a specific case. The second approach would check the value of an environment variable called "XARRAY_FORCE_PROMOTE" if it exists and set to true would force promoting type to float64. please tells us which approach suits best your vision of xarray. Regards. |
{
"total_count": 0,
"+1": 0,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
343659822 |